| Data Scientist- RTP, NC, OR San Jose, CA, -Need only local _Hybrid model at Remote, Remote, USA |
| Email: [email protected] |
| From: Sagar Kale, Digital Dhara [email protected] Reply to: [email protected] Role: Data Scientist- Hybrid model Location: RTP, NC , OR San Jose, CA, -Need only local Contract Job Summary: We are seeking a highly skilled and motivated Data Scientist to join our asset manager team. The Data Scientist will be responsible for developing, testing, and maintaining high-quality ML-based software applications using Python, Machine Learning libraries, Typescript, Web frameworks like React, and other relevant technologies. This role involves designing scalable solutions on AWS, supporting data-driven decision making, and integrating machine learning models with existing data pipelines. Key Responsibilities: ML Application Development: Develop, test, and maintain high-quality ML-based software applications using Python, Machine Learning libraries, Typescript, Web frameworks like React, and other relevant technologies. Scalable Solutions: Design and implement scalable and efficient solutions on AWS, ensuring robust performance and security. Data-Driven Decision Making: Support data-driven decision making by using Prefect for workflow orchestration and SQL, Snowflake for data warehousing. Model Development: Develop and deploy machine learning models using Python and relevant libraries/frameworks. Integration: Integrate machine learning solutions with existing data pipelines and DevOps practices. Production Management: Manage production-level code and ensure the reliability of machine learning models in a live environment. Containerization: Utilize Docker and Kubernetes for containerization and orchestration of applications. Collaboration: Collaborate with cross-functional teams to capture requirements, design solutions, and ensure successful project delivery. Support and Troubleshooting: Provide production support, troubleshoot issues, and implement fixes to ensure the smooth operation of software applications. Code Reviews and Best Practices: Participate in code reviews, contribute to standard methodologies, and continuously improve the development process. Industry Trends: Stay updated with the latest industry trends and technologies to ensure our solutions remain at the forefront of innovation. Who You Are: Passion for Data Science: You have a passion for data science and application development, thriving on innovation through the art of coding and storytelling. Team Player: You are an excellent team player who collaborates effectively with both technical colleagues and business partners. Hands-on Experience: You have hands-on experience with data science and machine learning techniques. Production Management: You have experience managing production-level code and deploying applications using Docker, Kubernetes, and Prefect/Airflow. Data Engineering and DevOps: You have good knowledge of data engineering and DevOps practices. Version Control: Experience with Git for version control and collaborative development. Proficient in SQL: Proficiency in SQL for data querying and manipulation. Strong Communication Skills: You possess strong communication skills and are adept at working collaboratively with team members and stakeholders. Problem-Solving Abilities: Exceptional problem-solving abilities and can thrive in a fast-paced environment. AWS and Cloud Architecture: In-depth knowledge of AWS services and cloud architecture. Workflow Orchestration: Proficient in using Prefect for workflow orchestration. Data Warehousing: Experience with Snowflake for data warehousing. Software Design Principles: Strong foundation in software design principles, algorithms, and data structures. Minimum Qualifications: Experience: 5+ years of Data Science with proficiency in Python and experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch). Technical Experience: 2+ years of experience in Technical Python, AWS, and data analysis tools such as SQL and Pandas. Preferred Qualifications: Education: Bachelor's degree in Computer Science, Engineering, or a related field. Additional Languages: Experience with other programming languages and frameworks. CI/CD and DevOps: Knowledge of CI/CD pipelines and DevOps practices. Data Engineering: Knowledge of data engineering practices and tools. Agile Methodologies: Familiarity with Agile methodologies and project management tools. Thanks & Regards, Sagar Kale sagar.k @digitaldhara.com Keywords: continuous integration continuous deployment machine learning California North Carolina Data Scientist- RTP, NC, OR San Jose, CA, -Need only local _Hybrid model [email protected] |
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| Tue Nov 12 22:58:00 UTC 2024 |